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ORCIDSomdatta Goswami
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2020 – today
- 2024
[j4]Varun Kumar
, Somdatta Goswami, Daniel Smith, George Em Karniadakis:
Real-time prediction of gas flow dynamics in diesel engines using a deep neural operator framework. Appl. Intell. 54(11-12): 14-34 (2024)- [j3]Qianying Cao, Somdatta Goswami, George Em Karniadakis:
Laplace neural operator for solving differential equations. Nat. Mac. Intell. 6(6): 631-640 (2024) - [c1]Katarzyna Michalowska, Somdatta Goswami, George Em Karniadakis, Signe Riemer-Sørensen:
Neural Operator Learning for Long-Time Integration in Dynamical Systems with Recurrent Neural Networks. IJCNN 2024: 1-8 - [i24]Bahador Bahmani, Somdatta Goswami, Ioannis G. Kevrekidis, Michael D. Shields:
A Resolution Independent Neural Operator. CoRR abs/2407.13010 (2024) - [i23]Luis Mandl, Somdatta Goswami, Lena Lambers, Tim Ricken:
Separable DeepONet: Breaking the Curse of Dimensionality in Physics-Informed Machine Learning. CoRR abs/2407.15887 (2024) - [i22]Varun Kumar, Somdatta Goswami, Katiana Kontolati, Michael D. Shields, George Em Karniadakis:
Synergistic Learning with Multi-Task DeepONet for Efficient PDE Problem Solving. CoRR abs/2408.02198 (2024) - [i21]Sharmila Karumuri, Lori Graham-Brady, Somdatta Goswami:
Efficient Training of Deep Neural Operator Networks via Randomized Sampling. CoRR abs/2409.13280 (2024) - [i20]Tyler Ingebrand, Adam J. Thorpe, Somdatta Goswami, Krishna Kumar, Ufuk Topcu:
Basis-to-Basis Operator Learning Using Function Encoders. CoRR abs/2410.00171 (2024) - 2023
- [j2]Katiana Kontolati, Somdatta Goswami, Michael D. Shields, George Em Karniadakis:
On the influence of over-parameterization in manifold based surrogates and deep neural operators. J. Comput. Phys. 479: 112008 (2023) - [i19]Somdatta Goswami, Ameya D. Jagtap, Hessam Babaee, Bryan T. Susi, George Em Karniadakis:
Learning stiff chemical kinetics using extended deep neural operators. CoRR abs/2302.12645 (2023) - [i18]Katarzyna Michalowska, Somdatta Goswami, George Em Karniadakis, Signe Riemer-Sørensen:
Neural Operator Learning for Long-Time Integration in Dynamical Systems with Recurrent Neural Networks. CoRR abs/2303.02243 (2023) - [i17]Qianying Cao, Somdatta Goswami, George Em Karniadakis:
LNO: Laplace Neural Operator for Solving Differential Equations. CoRR abs/2303.10528 (2023) - [i16]Katiana Kontolati, Somdatta Goswami, George Em Karniadakis, Michael D. Shields:
Learning in latent spaces improves the predictive accuracy of deep neural operators. CoRR abs/2304.07599 (2023) - [i15]Maria Luisa Taccari, He Wang, Somdatta Goswami, Jonathan Nuttall, Xiaohui Chen, Peter K. Jimack:
Developing a cost-effective emulator for groundwater flow modeling using deep neural operators. CoRR abs/2304.12299 (2023) - [i14]Nikolas Borrel-Jensen, Somdatta Goswami, Allan P. Engsig-Karup, George Em Karniadakis, Cheol-Ho Jeong:
Sound propagation in realistic interactive 3D scenes with parameterized sources using deep neural operators. CoRR abs/2308.05141 (2023) - [i13]Katarzyna Michalowska, Somdatta Goswami, George Em Karniadakis, Signe Riemer-Sørensen:
DON-LSTM: Multi-Resolution Learning with DeepONets and Long Short-Term Memory Neural Networks. CoRR abs/2310.02491 (2023) - 2022
- [j1]Somdatta Goswami, Katiana Kontolati, Michael D. Shields, George Em Karniadakis:
Deep transfer operator learning for partial differential equations under conditional shift. Nat. Mac. Intell. 4(12): 1155-1164 (2022) - [i12]Katiana Kontolati, Somdatta Goswami, Michael D. Shields, George Em Karniadakis:
On the influence of over-parameterization in manifold based surrogates and deep neural operators. CoRR abs/2203.05071 (2022) - [i11]Vivek Oommen, Khemraj Shukla, Somdatta Goswami, Rémi Dingreville, George Em Karniadakis:
Learning two-phase microstructure evolution using neural operators and autoencoder architectures. CoRR abs/2204.07230 (2022) - [i10]Somdatta Goswami, Katiana Kontolati, Michael D. Shields, George Em Karniadakis:
Deep transfer learning for partial differential equations under conditional shift with DeepONet. CoRR abs/2204.09810 (2022) - [i9]Somdatta Goswami, David S. Li, Bruno V. Rego, Marcos Latorre, Jay D. Humphrey, George Em Karniadakis:
Neural operator learning of heterogeneous mechanobiological insults contributing to aortic aneurysms. CoRR abs/2205.03780 (2022) - [i8]Ayan Chakraborty, Cosmin Anitescu, Somdatta Goswami, Xiaoying Zhuang, Timon Rabczuk:
Variational energy based XPINNs for phase field analysis in brittle fracture. CoRR abs/2207.02307 (2022) - [i7]Somdatta Goswami, Aniruddha Bora, Yue Yu, George Em Karniadakis:
Physics-Informed Deep Neural Operator Networks. CoRR abs/2207.05748 (2022) - [i6]Adar Kahana, Enrui Zhang, Somdatta Goswami, George Em Karniadakis, Rishikesh Ranade, Jay Pathak:
On the Geometry Transferability of the Hybrid Iterative Numerical Solver for Differential Equations. CoRR abs/2210.17392 (2022) - 2021
- [i5]Somdatta Goswami, Minglang Yin, Yue Yu, George E. Karniadakis:
A physics-informed variational DeepONet for predicting the crack path in brittle materials. CoRR abs/2108.06905 (2021) - [i4]Ritukesh Bharali, Somdatta Goswami, Cosmin Anitescu, Timon Rabczuk:
A robust monolithic solver for phase-field fracture integrated with fracture energy based arc-length method and under-relaxation. CoRR abs/2111.10649 (2021)
2010 – 2019
- 2019
- [i3]Somdatta Goswami, Souvik Chakraborty, Rajib Chowdhury, Timon Rabczuk:
Threshold shift method for reliability-based design optimization. CoRR abs/1904.11424 (2019) - [i2]Somdatta Goswami, Cosmin Anitescu, Souvik Chakraborty, Timon Rabczuk:
Transfer learning enhanced physics informed neural network for phase-field modeling of fracture. CoRR abs/1907.02531 (2019) - [i1]Esteban Samaniego, Cosmin Anitescu, Somdatta Goswami, Vien Minh Nguyen-Thanh, Hongwei Guo, Khader Hamdia, Timon Rabczuk, Xiaoying Zhuang:
An Energy Approach to the Solution of Partial Differential Equations in Computational Mechanics via Machine Learning: Concepts, Implementation and Applications. CoRR abs/1908.10407 (2019)
Coauthor Index
aka: George E. Karniadakis
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